Information Shock and Patient Roles in Medical Decision-Making

Last registered on April 30, 2025

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Pre-Trial

Trial Information

General Information

Title

Information Shock and Patient Roles in Medical Decision-Making

RCT ID

AEARCTR-0015749

Initial registration date

April 23, 2025

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published

April 30, 2025, 8:47 AM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Country

Austria

Region

Primary Investigator

Name

Silvia Angerer

Affiliation

UMIT TIROL - Private University for Health Sciences and Health Technology

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Other Primary Investigator(s)

PI Name

Johanna Kokot

PI Affiliation

University of Hamburg

Contact Investigator

PI Name

Claudia Schusterschitz

PI Affiliation

UMIT TIROL - Private University of Health Sciences and Health Technology

Contact Investigator

PI Name

Magdalena Flatscher-Thöni

PI Affiliation

UMIT TIROL - Private University of Health Sciences and Health Technology

Contact Investigator

Additional Trial Information

Status

In development

Start date

2025-04-23

End date

2025-05-02

Keywords

Behavior, Health

Additional Keywords

patient involvement medical decision-making, preferences, information shock

JEL code(s)

I1, D83, C99

Secondary IDs

Prior work

This trial is based on or builds upon one or more prior RCTs.

Abstract

An important aspect of healthcare use and outcomes lies in the quality of the physician-patient relationship with better perceived quality leading to better outcomes. There is a growing body of research suggesting a more active involvement of patients in medical decision-making, such as shared decision-making to improve the quality of physician-patient interactions .Though patients report preferences to be involved in medical decision-making and research highlights the variability of these preferences across individual-specific factors, it remains unclear how the general population is actually involved in medical decision-making and how the preferences for patient involvement is shaped by an information shock regarding physician behavior.

External Link(s)

Registration Citation

Citation

Angerer, Silvia et al. 2025. "Information Shock and Patient Roles in Medical Decision-Making." AEA RCT Registry. April 30. https://doi.org/10.1257/rct.15749-1.0

Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)

There are two different experimental groups:
Group 1 (Baseline): No information provision,
Group 2 (Information): Information about physician recommendations that contradicts clinical guidelines - as measured in a previous survey experiment (Angerer, 2024) is provided.

Angerer, Silvia. 2024. "The role of beliefs in the supply of health screenings." AEA RCT Registry. June 24. https://doi.org/10.1257/rct.13729-1.0

Intervention (Hidden)

There are two different experimental groups:
Group 1 (Baseline): No information provision
Group 2 (Information): Information is provided showing that 81% of general practitioners recommend PSA testing for all men aged 50 and older. This figure is based on a previous survey experiment conducted among general practitioners in Austria (Angerer, Silvia, 2024). Additionally, information is included stating that PSA testing for the early detection of prostate cancer is not recommended as a general screening program, as the potential harms outweigh the benefits.

Angerer, Silvia. 2024. "The role of beliefs in the supply of health screenings." AEA RCT Registry. June 24. https://doi.org/10.1257/rct.13729-1.0

Intervention Start Date

2025-04-23

Intervention End Date

2025-05-02

Primary Outcomes

Primary Outcomes (end points)

Preferences for patient involvement using the Control Preference Scale (CPS).

Primary Outcomes (explanation)

The scale assesses preferences by asking respondents to choose one of five options, ranging from an active patient role (otions 1/2), through shared decision-making (option 3), to a passive patient role (options 4/5).

The outcome is treated as a categorical variable with three categories, as an indicator variable and as an continuous variable. The indicator is treated as passive role (1) vs. not. The categorical variable is coded as: (1) active role, (2) shard decision-making , (3) passive role. And the continuous variable uses the answers with the five orderings from active (1) to passive (5).

Secondary Outcomes

Secondary Outcomes (end points)

Trust in general practitioners is measured using 4 items of the TPS (Trust in Physicians Scale).

Secondary Outcomes (explanation)

The scale consists of 11 items rated on a 5-point Likert scale to assess levels of agreement. For the purposes of the following research question, four items identified as most relevant will be selected and combined into a composite index. This variable serves as secondary outcome as well as potential mediator.

Experimental Design

Online survey experiment comprises random assignment of people from the general population aged 18 to 75 years in Austria to one of two experimental groups: (i) No information, (ii) Information. The sample is (online) representative of the general population with respect to age, gender, education and federal state.

Experimental Design Details

Randomization Method

Randomization done by computer program used for the survey.

Randomization Unit

Individual randomization to one of two experimental groups.

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

1,000 units (individuals)

Sample size: planned number of observations

1.000 individuals (no clustered design)

Sample size (or number of clusters) by treatment arms

500 individuals for each treatment arm

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Categorical variable: Using multinomial logistic regression with the passive role as the reference category, the minimum detectable effect size is an odds ratio of 1.65 for both active and shared decision-making roles relative to the passive role in the treatment group using a simulation-based approach with a power of 0.8 and 1,000 individuals (500 per treatment arm). Binary variable: With a power of 0.8, alpha 0.05 and the sample size of 1.000, the minimum detectable effect size is a delta of 0.0885 (8.85 percentage points). Ordinal (treated as continuous from 1 to 5): With a power of 0.8, alpha 0.05 and the sample size of 1.000, the minimum detectable effect size is 0.1774 standard deviations.

Supporting Documents and Materials

IRB